112 citations · 311 across the 23 of their papers we have counts for
7 papers · 1 filter
Predictive inference for discrete-valued time series
Maxime Faymonville, Carsten Jentsch, Efstathios Paparoditis
For discrete-valued time series, predictive inference cannot be implemented through the construction of prediction intervals to some predetermined coverage level, as this is the ca…
Frequency Domain Statistical Inference for High-Dimensional Time Series
Jonas Krampe, Efstathios Paparoditis
Analyzing time series in the frequency domain enables the development of powerful tools for investigating the second-order characteristics of multivariate processes. Parameters lik…
A Frequency Domain Bootstrap for General Multivariate Stationary Processes
Marco Meyer, Efstathios Paparoditis
For many relevant statistics of multivariate time series, no valid frequency domain bootstrap procedures exist. This is mainly due to the fact that the distribution of such statist…
Structural Inference in Sparse High-Dimensional Vector Autoregressions
Jonas Krampe, Efstathios Paparoditis, Carsten Trenkler
We consider statistical inference for impulse responses in sparse, structural high-dimensional vector autoregressive (SVAR) systems. We introduce consistent estimators of impulse r…
A Frequency Domain Bootstrap for General Stationary Processes
Marco Meyer, Efstathios Paparoditis, Jens-Peter Kreiss
Existing frequency domain methods for bootstrapping time series have a limited range. Consider for instance the class of spectral mean statistics (also called integrated periodogra…
Bootstrap Based Inference for Sparse High-Dimensional Time Series Models
J. Krampe, J-P. Kreiss, E. Paparoditis
Fitting sparse models to high-dimensional time series is an important area of statistical inference. In this paper we consider sparse vector autoregressive models and develop appro…